An IT industry insider's perspective on information, technology and customer challenges.

January 11, 2012

Building Your IT Factory

Analogies can be powerful tools. The good ones are descriptive: sort of an intellectual shortcut to a set of concepts and ideas. They save time.

But I think the very best analogies can become predictive models: you can examine them at length and come up with all sorts of useful, forward-looking insights that can make you look eerily prescient.

If you want to impress people with your crystal ball skills, have a good predictive model or two in your back pocket :)

Such is the case with IT's current transformation to becoming a competitive internal service provider.

In his landmark book "The Big Switch", Nicholas Carr uses the early days of the power generation and distribution industry as a powerful analogy for understanding what was beginning to happen with cloud computing.

In many aspects, his analogy was a decent predictive model: you could examine how the power industry began, evolved and matured -- and make some interesting predictions about how similar things might happen in the cloud and IT world.

Even if you don't believe in cloud, Nick Carr (or anything else for that matter!) his recounting of the evolution of the power industry is fascinating and insightful.

However, it's been three long years since Nick published his book -- a veritable eternity in our industry -- and I think I can now suggest a better analogy that's proving to be far more powerful in its predictive power.

Indeed, as I spend more and more time with customers talking about their current transformations, I find myself using factory-based analogies more often to describe concepts and principles. It works.

And, since so many IT leaders I work with have to explain many things to the people in their world, I thought I'd take the time to expand the analogy.

Hopefully it will work for them as well as it's worked for me.

Origins

If you're a regular reader, you know the back story. IT organizations are being forced to compete against increasingly attractive external options. As they learn to compete, major changes are inevitable: new models, new skills, new roles, new processes -- indeed, an entirely new culture for many.

Simply put, it's IT Transformation with a capital "T".

I am extremely fortunate in being able to use EMC IT's own transformation experiences as a meaningful guidepost for others. Yes, we're different, but we're not all that different. The lessons we've learned are turning out to be broadly applicable to many.

However, IT is not the first (nor is it the last) industry to go through this sort of transformation. If you're a student of business history, examples are everywhere. And there undoubtedly will be more.

One of the key actors from EMC IT is Jon Peirce, who -- almost serendipitously -- came from the manufacturing industry where he led a strikingly similar transformation prior to joining the IT world. He frequently uses factory and manufacturing examples to describe concepts. They're turning out to be pretty darn good examples.

So, grab a cup of coffee (or a beer) and let's unpack the "factory analogy" for IT transformation.

If it helps you in your efforts, I've done my job.

The Black Box Abstraction

At one level, a factory is a building where unfinished materials go in, and value-add comes out. It's a place where value is added -- almost a fundamental construct of our economic thinking.

For starters, it must compete with others who are doing the same. People have to prefer (and be willing to pay for) the unique type of value add that comes out of a specific factory, as opposed to another one. Fail to secure paying customers, and the factory won't be around for very long.

Factories these days are almost always part of an extended value chain. From raw materials to consumable goods, the output of one factory is often input to the next one. For example, even though EMC manufactures storage arrays, we've got an extended supply chain of sub-assemblies behind us, and our output (e.g. a storage array) is occasionally the input for an OEM or reseller building a finished system for a customer.

As factories focus on their unique value-add, it always raises the question of what is better done by one factory, and what would be better done by someone else's. Indeed, someone in the manufacturing industry who insisted in doing everything themselves would be looked on as sort of a curious anachronism.

Continuing our black-box abstraction, other inputs are (1) people, (2) capital and (3) expertise. Obviously, the goal with people and capital is to get the most value-add possible as compared to your competition. This might mean hiring cheaper people, or (more frequently) a fewer number of skilled people who can be more productive. supported by capital investment (think automation).

If you're an armchair student of economics, you'd probably agree with observation that we saw a lot of labor arbitrage in the past few decades (moving manufacturing to low-cost economies where semi-skilled labor was cheaper) which is now being replaced by a repatriation to economies where the advanced skills required for highly automated environments are available.

That's true for manufacturing as well as IT :)

Opening The Black Box

Crack open any successful factory, and you'll see a continuing and ongoing investment in process: measurement, analysis, experimentation, maturation and continual improvement. Indeed, it's a truism in the manufacturing industry that "you're only as good as your processes" hence an ongoing and passionate focus on continual process improvement.

There are demand processes -- what do my customers want? -- both in the types of goods I'm producing, as well as their quantity. There are supply processes -- how can I leverage my supply chain to be more competitive and responsive? There are people processes -- how can I make my workforce more valuable? There are the inevitable cost and quality processes -- an ongoing treadmill.

Looking a little deeper, there's a meta-process involved: the process of continually re-examining and improving how the various processes interact. Indeed, manufacturing is a veritable intellectual playground for those that really like understanding and improving processes.

The rationale for continuous process improvement should be obvious. If you don't invest in continually improving your processes, your competitors will. And you won't be a successful factory for very long as your customers will go elsewhere :(

Automation, Baby!

In manufacturing, once a process is well understood, the investment case is made for automating it.

Note that automation isn't applied until the process is fairly well understood. Usually, it's automated in a modular and componentized way that still preserves flexibility and agility for making further process improvements down the road. It's just assumed that the best approach for automation today won't necessarily be the best approach tomorrow -- and having the agility to make further improvements is core to being a successful manufacturer.

Many of your workers are trained and skilled at working in a highly automated environment. They're looking at status and dashboards vs. getting their hands directly in the plumbing, unless there's a serious problem. Since the factory is continually improving their processes, they're also continually improving their automation, which means that operational workers are always learning something new :)

And Lots Of (Big) Data

Automated operations produce mountains of data on activities and results. These feeds are the raw input to the analysts who are continually looking for opportunities to re-engineer and improve the operational processes that are at the core of the factory's competitive advantage.

But -- as with most things -- most of the really interesting data lies outside of the factory floor. What's going on with customers? What's going on with my supply chain? Logistics? The economy? The weather? The government?

Since factories need time to react to new events and opportunities, they greatly value any sort of predictive function. Indeed, the predictive value of big data analytics is finding a strong foothold in many large-scale manufacturing operations -- simply because they can compete better if they know what's probably going to happen before their competitors do.

Back To The World Of IT

At one level, a data center can be thought of a black box where value is created. Inputs in, valuable services out.

They compete with others doing the same. Just as no factory has a right to exist, neither does a data center, or an IT organization for that matter.

Data centers have to figure out what their customers want, and do it better than the alternatives. They have to leverage their supply chain to maximize their unique value add, including perhaps using other data centers run by others.

The heavy intellectual work will be around continual process improvement: supported by automation and analytics. Demand processes, supply processes, quality processes, cost processes, compliance processes, etc. At one level, any IT organization will only be as good as their processes, just as is true in the manufacturing world.

The skills and talents required will inevitably mature and evolve towards a smaller number of more highly compensated people who can deliver unique productivity as comapred to using semi-skilled labor.

Just as with manufacturing, there will be continual stream of technological advances that must be understood, evaluated and frequently put into practice -- hopefully, before your competitors learn to do the same.

Once IT competes for their internal customers, there's really no turning back.

The same powerful forces that have morphed and shaped other industries will work their gravitational effect on all participants: vendors and customers alike.

IT will inevitably follow the same evolutionary path as other value-added activities. In some aspects, the future is very clear indeed.

Continual Transformation -- The New IT Norm?

Several years ago, I visited an auto manufacturing plant at one of EMC's customers. As a card-carrying geek, I was duly impressed by the degree of automation and process engineering. I was particularly impressed with the closed-loop continual improvement processes being used.

I recently revisited that same place. It was almost unrecognizable.

The products had changed. Almost all of the processes. The level and focus areas of automation. The basic architecture of the plant had changed. The tasks they did vs. others in the supply chain. And more, I'm sure.

I turned to my host, and expressed my amazement at the degree of rapid evolution as compared to just a few short years ago.

Comments

I'm constantly amazed by how much similarities are there between successful IT organizations and the operational culture of a successful startup. The "automation and process engineering" and "closed-loop continual improvement processes" are so critical, regardless if you are $19B/year company or a bootstrapped business. For IT Renaissance to really become reality (http://mark.chmarny.com/2011/11/corporate-it-oblivious-to-new-role-but.html), it needs to learn how to pivot on demands while maintaining their long-term vision.

Thanks Chuck for yet another in-depth look at challenging areas of our industry, too often blog posts on subject like this are oversimplified with a quick "you are doing it wrong" sign off.

PS. Yep, I did just finished reading The Lean Startup: How Today's Entrepreneurs Use Continuous Innovation to Create Radically Successful Businesses.